import torch
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

def himmelblau(x):
  return (x[0] ** 2 + x[1] - 11) ** 2 + (x[0] + x[1] ** 2 -7) ** 2

x = np.arange(-6, 6, 0.1)
y = np.arange(-6, 6, 0.1)
print('x,y range:', x.shape, y.shape)
X, Y = np.meshgrid(x,y)
print('X, Y maps:', X.shape, Y.shape)
Z = himmelblau([X, Y])

fig = plt.figure()
ax = Axes3D(fig)
ax = fig.add_subplot(111, projection='3d')
# ax = fig.gca(projection='3d')
ax.plot_surface(X, Y, Z)
ax.view_init(60, -30)
ax.set_xlabel('x')
ax.set_ylabel('y')
plt.show()


x = torch.tensor([0.,0.], requires_grad=True)
optimizer = torch.optim.Adam([x], lr=1e-3)
for step in range(20000):
  pred = himmelblau(x)
  optimizer.zero_grad()
  pred.backward()
  optimizer.step()

  if step % 2000 == 0:
    print('step {}: x = {}, f(x) = {}'.format(step, x.tolist(), pred.item()))